The Space Telescope Imaging Product Simulator (STIPS) is a versatile tool designed to simulate exposure level astronomical scenes from the Wide Field Instrument (WFI) for Roman. This article presents a few simple examples on the functionalities of STIPS. Users can find a more extensive list of tutorials and examples in the form of python jupyter notebooks on the Roman Research Nexus (RRN). Additional information is available from the tool's online documentation and by consulting the published paper.

The Basic STIPS Usage Tutorial builds on the concepts introduced in the Overview of STIPS article and is designed to walk through the phases of using  STIPS at the most introductory level: (1) creating a small astronomical scene; (2) designing an observation; and (3) generating a simulated image. 

Example 1: Generating a Simple Astronomical Scene

STIPS provides functionalities to generate catalogs of stars or galaxies with user-specified input parameters. Users can also provide their own source catalogs, as described in Catalogs formatting on readthedocs.

In the example below, we show how to create an astronomical scene by passing the user-defined input catalogs to STIPS in the FITS format. The catalog contains the coordinates of the sources, the observed flux, and any necessary shape parameters. The code block below provides an example of the required input information to generate a catalog containing two point sources. The catalog is saved to a file called catalog.fits for later use.

from astropy.io import fits

cols=[]
cols.append(fits.Column(name='id'   ,array=[1,2]            , format='K' )) # Object ID
cols.append(fits.Column(name='ra'   ,array=[90.02,90.03]    , format='D' )) # RA in degrees
cols.append(fits.Column(name='dec'  ,array=[29.98,29.97]    , format='D' )) # DEC in degrees
cols.append(fits.Column(name='flux' ,array=[0.00023,0.0004] , format='D' )) # Flux in `units`
cols.append(fits.Column(name='type' ,array=['point','point'], format='8A')) # `point` or `sersic`
cols.append(fits.Column(name='n'    ,array=[0,0]            , format='D' )) # Sersic profile index
cols.append(fits.Column(name='re'   ,array=[0,0]            , format='D' )) # Half-light radius in pixels
cols.append(fits.Column(name='phi'  ,array=[0,0]            , format='D' )) # Angle of PA in degrees
cols.append(fits.Column(name='ratio',array=[0,0]            , format='D' )) # Axial Ratio
cols.append(fits.Column(name='notes',array=['','']          , format='8A')) # Notes
cols.append(fits.Column(name='units',array=['j','j']        , format='8A')) # Units, 'j' for jansky

# Create output fits table
hdut = fits.BinTableHDU.from_columns(cols)
hdut.header['TYPE']='mixed'
hdut.header['FILTER']='F129'

# Write to disk
hdut.writeto('catalog.fits',overwrite=True)

The output of this code block is a FITS table containing the generated catalog of sources.

Example 2: Observation Setup

Next, we prepare inputs for the scene we created above. We use the ObservationModule  to generate an observation object. We generate an obs dictionary containing the properties of the observation (e.g. the instrument and the detector setups) and parameters describing central coordinates (R.A., Dec.), position angle (PA), and computational parameters for the simulation. 

The Observation Dictionary

An example  obs dictionary is specified in the code block below. In this example,  we select: 

• The imaging filter F129
• The WFI01 detector
• Sky background from Pandeia
• An observation ID of 42
• An exposure time of 300 seconds

Together with the following single offset setting:

• An offset ID of 1
• No centering
• No changes in R.A., Dec., and PA from the center of the observation

from stips.observation_module import ObservationModule

# Build observation parameters
obs = {'instrument'       : 'WFI',
       'filters'          : ['F129'],
       'detectors'        : 1,
       'background'       : 'pandeia',
       'observations_id'  : 42,
       'exptime'          : 300,
       'offsets'          : [{'offset_id'    : 1    ,
                              'offset_centre': False,
                              'offset_ra'    : 0.0  ,
                              'offset_dec'   : 0.0  ,
                              'offset_pa'    : 0.0  }]}

The Observation Object

An observation object combines the obs dictionary with the central coordinates (RA, Dec), orientation angle, and computational parameters for the simulation. Then, the setup can be initialized.

# Create observation object
obm = ObservationModule(obs,
                        ra    = 90,
                        dec   = 30,
                        pa    = 0,
                        seed  = 42,
                        cores = 6)

Example 3: Generating a Simulated Image

The code block below combines the inputs required for STIPS that were generated above and finalizes the ObservationModule to run a simulation. The final simulated image will be saved under the name specified by the  fits_file variable, and the result is shown on the right.

For additional questions not answered in this article, please contact the Roman Help Desk.

References

• Roman Research Nexus: https://roman.science.stsci.edu/hub/
• STIPS on readthedocs: https://stips.readthedocs.io/en/latest/
• STIPS on Github: https://github.com/spacetelescope/STScI-STIPS/tree/main
• STIPS Development Team et al 2024, "STIPS: The Nancy Grace Roman Space Telescope Imaging Product Simulator", PASP 136 124502